Książki

This book contains high-quality peer-reviewed papers of the International Conference on Big Data, Machine Learning and their Applications (ICBMA 2019) held at Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India, during 29-31 May 2020. The book provides significant contributions in a structured way so that prospective readers can understand how these techniques are used in finding solutions to complex engineering problems. The book covers the areas of big data, machine learning, bio-inspired algorithms, artificial intelligence and their applications.

Proceedings of International Conference on Big Data, Machine Learning and their Applications: ICBMA 2019

Chapter 1. Analysis of Efficiency of Fractional order Technique in a Controller for a complex Non-Linear Control Process.- Chapter 2. NWP models combined with Ensemble Models for Hourly Estimation of Global Solar Irradiance.- Chapter 3. Literature Review on Agricultural Internet of Things.- Chapter 4. Deep Learning approach based Network Intrusion Detection System for fog assisted IoT.- Chapter 5. Improving Prediction Accuracy for Debonding Quantification in Stiffened Plate by Meta Learning Model.- Chapter 6. The Need of Advanced Assisting Devices for Blind People.- Chapter 7. A Noval Fuzzy based Artificial Bee Colony Algorithm for Medical Records Classification.- Chapter 8. A comparative study: Glaucoma detection using deep neural networks.- Chapter 9. Security Risks and Challenges in IoT Based Applications.- Chapter 10. An Assessment of Type-2 Diabetes Risk Prediction using Machine Learning- A Review.- Chapter 11. Comparative Study of Different Reduced Precision Techniques in Deep Neural Network.- Chapter 12. A study of Predictive Measures in Neural Network Architectures for Plant Disease Detection.- Chapter 13. Design and Analysis of Smart Automatic Street Light System.- Chapter 14. Combating DDoS attack on OpenStack using Hypervisor based intrusion detection system with the help of machine learning.- Chapter 15. Exploring Honeycomb Interconnection Networks.